Algorithms & Data Structures
2026 Exam Questions with
100% Correct Answers | Latest
Update
Greedy Algorithm - ANSWER ✔✔an algorithm that follows problem
solving heuristic of making optimal choices at each stage. Hopefully
finds the global optimum. An example would be Kruskal's algorithm.
Divide and Conquer - ANSWER ✔✔works by recursively breaking
down a problem into two or more sub problems until the problems
,become simple enough to be solved directly. An example would be
mergesort.
Recursive Algorithms - ANSWER ✔✔solve a problem by solving
smaller internal instances of a problem -- work towards a base case.
Dynamic Programming - ANSWER ✔✔Break down a problem into
smaller and smaller subproblems. At their lowest levels, the
subproblems are solved and their answers stored in memory. These
saved answers are used again with other larger (sub)problems which
may call for a recomputation of the same information for their own
answer. Reusing the stored answers allows for optimization by
combining the answers of previously solved subproblems.
Selection Sort - ANSWER ✔✔Non-stable, in place sort. Has an N-
squared order of growth, needs only one spot of extra space. Works by
searching the entire array for the smallest item, then exchanging it with
the first item in the array. Repeats this process down the entire array
until it is sorted.
Insertion Sort - ANSWER ✔✔Stable, in place sort with an order of
growth which is between N and N-squared, needs only one spot of extra
space and is dependent on the order of the items. Works by scanning
over the list, then inserting the current item to the front of the list where it
,would fit sequentially. All the items to the left of the list will be sorted, but
may not be in their final place as the larger items are continuously
pushed back to make room for smaller items if necessary.
ShellSort - ANSWER ✔✔Non-stable, in place sort with an order of
growth which is undetermined, though usually given at being N-to-the
6/5. Needs only one spot of extra space. Works as an extension of
insertion sort. It gains speed by allowing exchanges of entries which are
far apart, producing partially sorted arrays which are eventually sorted
quickly at the end with an insertion sort. The idea is to rearrange the
array so that every h-th entry yields a sorted sequence. The array is h-
sorted.
Quick Sort - ANSWER ✔✔Non-stable, in place sort with an order of
growth of NlogN. Needs lgN of extra space. It has a probabilistic
guarantee. Works by making use of a divide and conquer method. The
array is divided into two parts, and then the parts are sorted
independently. An arbitrary value is chosen as the partition. Afterwards,
all items which are larger than this value go to the right of it, and all
items which are less than this value go to the left of it.
3
COPYRIGHT©JOSHCLAY 2025/2026. YEAR PUBLISHED 2026. COMPANY REGISTRATION NUMBER: 619652435. TERMS OF USE. PRIVACY
STATEMENT. ALL RIGHTS RESERVED
, We arbitrarily choose a[lo] as a partitioning item. Then we scan from the
left end of the array one by one until we find an entry that is greater than
a[lo]. At the same time, we are scanning from a[lo] to the right to find an
entry that is less than or equal to a[lo]. Once we find these two values,
we swap them.
3-Way Quick Sort - ANSWER ✔✔Non-stable, in place sort with an
order of growth between N and NlogN. Needs lgN of extra space. Is
probabilistic and dependent on the distribution of input keys.
Mergesort - ANSWER ✔✔Stable sort which is not in place. It has an
order of growth of NlogN and requires N amount of extra space. Works
by dividing an array in half continuously into smaller and smaller arrays.
At the lowest level, these arrays are sorted and then merged together
after sorting in the reverse order they were divided apart in.
Heap Sort - ANSWER ✔✔Non-stable, in place sort which has an
order of growth of NlogN. Requires only one spot of extra space. Works
like an improved version of selection sort. It divides its input into a sorted
and unsorted region, and iteratively shrinks the unsorted region by
extracting the smallest element and moving it into the sorted region. It
will make use of a heap structure instead of a linear time search to find
the minimum.
2026 Exam Questions with
100% Correct Answers | Latest
Update
Greedy Algorithm - ANSWER ✔✔an algorithm that follows problem
solving heuristic of making optimal choices at each stage. Hopefully
finds the global optimum. An example would be Kruskal's algorithm.
Divide and Conquer - ANSWER ✔✔works by recursively breaking
down a problem into two or more sub problems until the problems
,become simple enough to be solved directly. An example would be
mergesort.
Recursive Algorithms - ANSWER ✔✔solve a problem by solving
smaller internal instances of a problem -- work towards a base case.
Dynamic Programming - ANSWER ✔✔Break down a problem into
smaller and smaller subproblems. At their lowest levels, the
subproblems are solved and their answers stored in memory. These
saved answers are used again with other larger (sub)problems which
may call for a recomputation of the same information for their own
answer. Reusing the stored answers allows for optimization by
combining the answers of previously solved subproblems.
Selection Sort - ANSWER ✔✔Non-stable, in place sort. Has an N-
squared order of growth, needs only one spot of extra space. Works by
searching the entire array for the smallest item, then exchanging it with
the first item in the array. Repeats this process down the entire array
until it is sorted.
Insertion Sort - ANSWER ✔✔Stable, in place sort with an order of
growth which is between N and N-squared, needs only one spot of extra
space and is dependent on the order of the items. Works by scanning
over the list, then inserting the current item to the front of the list where it
,would fit sequentially. All the items to the left of the list will be sorted, but
may not be in their final place as the larger items are continuously
pushed back to make room for smaller items if necessary.
ShellSort - ANSWER ✔✔Non-stable, in place sort with an order of
growth which is undetermined, though usually given at being N-to-the
6/5. Needs only one spot of extra space. Works as an extension of
insertion sort. It gains speed by allowing exchanges of entries which are
far apart, producing partially sorted arrays which are eventually sorted
quickly at the end with an insertion sort. The idea is to rearrange the
array so that every h-th entry yields a sorted sequence. The array is h-
sorted.
Quick Sort - ANSWER ✔✔Non-stable, in place sort with an order of
growth of NlogN. Needs lgN of extra space. It has a probabilistic
guarantee. Works by making use of a divide and conquer method. The
array is divided into two parts, and then the parts are sorted
independently. An arbitrary value is chosen as the partition. Afterwards,
all items which are larger than this value go to the right of it, and all
items which are less than this value go to the left of it.
3
COPYRIGHT©JOSHCLAY 2025/2026. YEAR PUBLISHED 2026. COMPANY REGISTRATION NUMBER: 619652435. TERMS OF USE. PRIVACY
STATEMENT. ALL RIGHTS RESERVED
, We arbitrarily choose a[lo] as a partitioning item. Then we scan from the
left end of the array one by one until we find an entry that is greater than
a[lo]. At the same time, we are scanning from a[lo] to the right to find an
entry that is less than or equal to a[lo]. Once we find these two values,
we swap them.
3-Way Quick Sort - ANSWER ✔✔Non-stable, in place sort with an
order of growth between N and NlogN. Needs lgN of extra space. Is
probabilistic and dependent on the distribution of input keys.
Mergesort - ANSWER ✔✔Stable sort which is not in place. It has an
order of growth of NlogN and requires N amount of extra space. Works
by dividing an array in half continuously into smaller and smaller arrays.
At the lowest level, these arrays are sorted and then merged together
after sorting in the reverse order they were divided apart in.
Heap Sort - ANSWER ✔✔Non-stable, in place sort which has an
order of growth of NlogN. Requires only one spot of extra space. Works
like an improved version of selection sort. It divides its input into a sorted
and unsorted region, and iteratively shrinks the unsorted region by
extracting the smallest element and moving it into the sorted region. It
will make use of a heap structure instead of a linear time search to find
the minimum.
